Method and device for removing narrow band interference in spreading frequency system

ABSTRACT

Narrow-band interference in spread spectrum systems is eliminated by performing a frequency spectrum transform on N sampling points of the data to obtain N points of data; after M transforms, getting an energy accumulation of individual data to obtain N energy values; removing partial excessive large values from the N energy values, averaging the rest, then calculating the threshold value for interference determination based on the average value; identifying all points that have energy values exceeding the threshold value, and performing interference suppression for the data of corresponding points after frequency spectrum transform and finally outputting the data after frequency spectrum inverse transform.

TECHNICAL FIELD

The present invention pertains to spread spectrum technology used in awireless communication system, specifically to a method and device foreliminating narrow-band interference.

TECHNOLOGY BACKGROUND

The spread spectrum communication system is widely used nowadays. Thespread spectrum or the pseudo-random (PN) code modulation can decreasethe interference from other users and wireless signals. During thecross-correlation process of received signals and PN sequence, when theinterference is a narrow-band signal, the interference, signals willspread to the entire band and thus weaken the impact of theinterference. As a result, the spread spectrum signals could weaken thenarrow-band interference to some extend.

The typical spectrum of a spread spectrum signal (e.g. performing spreadspectrum from PN sequence) is submerged in the noise, as shown inFIG. 1. Ideal signal is the signal energy that is actually sent out bythe mobile station and noise is the additive interference. Obviously,the ideal signal energy of the spread spectrum is usually less than thenoise energy. The “strong interference” generally refers to the blockingsignals or the signals that are sent out by TV, wireless station andnearby communication equipments. “Typical interference” refers to thesignals sent out by those low-power sources, such as amateur radio.Processing gain represents the level of the interference signalstolerable by the spread signals in mobile station. The spread signalscan still be recovered when they are affected by the typicalinterference, but they will never be recovered when the stronginterference shows up. What's more, even with the typical interference,the system performance will degrade thought the signals can berecovered.

Before utilizing CDMA communication system, the frequency band will beswept in order to protect the CDMA signals from the interference ofnarrow-band signals. However, since some burst signals are hard to befully forbidden due to their burst characteristics, the narrow-bandinterference will present disorder and randomicity. The narrow-bandinterference will increase the congestion rate and call-dropping rate ina CDMA system, overload the radio-frequency power control system,increase the power consumption of mobile station and reduce the basestation coverage. Under extreme situation, the high-power interferencewill even block the entire cell, and thus the normal communication willstop. As a result, a good solution have to be found in order toeliminate the impact of the narrow-band interference signals on the CDMAsignals and guarantee good quality of the communication.

Generally, methods for dealing with narrow-band interference are dividedinto two categories:

The first category is to make the signal (usually under analogprocessing) pass through a narrow-band notch filter or filter group.This method is usually realized by the surface acoustic technology, inwhich the estimation for the frequency of interference signals is madeand based on the estimation result, a narrow-band notch filter is placedwhere there are interference signals (the PLL (phase locked loop) canalso be used to track the interference signals). However, the analogtechnology has its own limitations, and usually lacks flexibility.

Another kind of methods is frequency domain elimination which isgenerally realized through digital processing. Signals are firstdigitized and then transformed into frequency domain through FourierTransform. These data will be processed in the frequency domain andfinally be transformed back into the time domain to be output throughinverse-Fourier Transform. The methods for processing interferencesignals in the frequency domain can be summarized into two types: thefirst one is to filter out the interference impact through the filter onthe frequency domain data and this method is suitable when the bandwidthand location of the interference are already known, but this method willhave a certain limitation when the interference location in thefrequency domain, the bandwidth and the number of the interferences arehard to identify, since there is a certain degree of difficulty indesigning a fully adaptive filter.

Another type is to compute the signal amplitude on each frequency pointand then compares them with the threshold value. Signals exceeding thethreshold values are considered as narrow-band interference signals andwill be set as zero or be degraded to noise level. This method couldadaptively process multiple interference, multiple interferencebandwidths and interference frequency changes, but whether the thresholdsetting in this method is good or not will directly affect itsperformance. The common way of setting threshold is to calculate theaverage value of the energies or amplitudes of all the data that aretransformed into frequency domain and multiply that average value with afixed multiple, so the computed average value will be the main criteriain setting up the threshold. This method of setting threshold value willbe subject to the impacts of the magnitude and the number of narrow-bandinterferences, because the obtained average value will have acorresponding increase when the energy and the number of the narrow-bandinterferences increase. Therefore it can not reflect the realperformance of the energy of non-interference data and decrease theperformance in interference suppression.

SUMMARY OF THE INVENTION

The technical problem that needs to be solved in present invention is toprovide a method and device for eliminating narrow-band interference ina spread spectrum system, which could exactly distinguish interferencedata from non-interference data and thus effectively suppressnarrow-band interference. The present invention also needs to provide adevice that can realize the above method.

In order to solve the above technology problem, the present inventionprovides a method for eliminating narrow-band interference in a spreadspectrum system, which comprises the following steps of:

(A) extracting N sampling points of data to perform frequency spectrumtransform each time and obtaining the transformed N points of the data;

(B) for the N sampling points, getting the energy accumulation ofindividual data after transform for M times and obtaining N energyvalues, wherein M is the integer greater than or equal to 1;

(C) removing partial excessive large values from the N energy values andaveraging the rest, then calculating a threshold value for interferencedetermination based on the average value;

(D) comparing the N energy values with the threshold value, andobtaining identification information of all the points that have energyvalues exceeding the threshold;

(E) based on the identification information of said points, performinginterference suppression for the data of the corresponding points afterfrequency spectrum transform and finally outputting the data afterfrequency spectrum inverse transform.

Moreover, the above method also possesses following features: in saidstep (C), it first sequences the N energy values and removes K largestenergy values, wherein K is computed in one of the following methods:

$\begin{matrix}{{K = {{ceil}( {\sum\limits_{i = 1}^{N_{li}}{\frac{f_{li}}{f_{s}}*N}} )}},} &  a )\end{matrix}$wherein N_(I) is the estimated number of narrow-band interferences;f_(Ii) is the estimated bandwidth of the i^(th) narrow-bandinterference; f_(S) is the sampling frequency of the input data. “ceil ()” means rounding towards plus infinity.

b) K is the integer that is larger than 0.25N and less than 0.35N;

c) K is the number of the energy values that are larger than thethreshold in said N energy values in the last computation;

d) K=N−1, means directly using the minimum energy value as said averagevalue.

Additionally, the above method also possesses the following feature: insaid step (C), it removes not only partial excessive large energyvalues, but also excessive small energy values as well, and thenaverages the rest.

Additionally, the above method also possesses the following feature: insaid step (C), the average value is multiplied with 3-3.5 to be saidthreshold value.

Additionally, the above method also possesses the following features: insaid step (B), M is determined by the number of sampling cycles includedin an accumulation time period, and in step (E) when processing theinterference elimination for the data in an accumulation time period,the points in which the interference suppression is needed to beperformed are determined based on the identification information of thepoints with energy values larger than said threshold recorded in thelast accumulation time period.

Additionally, the above method also possesses the following feature: theaccumulation time period is of 60-120 ms. Additionally, the above methodalso possesses the following features: in step (E) when suppressing datainterference, it is to reduce the energy values of the data atinterference points to the time average value of the minimum energyvalue within said N energy values or it is to reduce the energy valuesof the data at interference points to the time average value of saidaverage values.

The present invention provides a device for eliminating narrow-bandinterference in a spread spectrum system, and the device comprises afrequency spectrum transform unit, an interference elimination unit, aninterference elimination control unit and a frequency spectrum inversetransform unit, wherein:

said frequency spectrum transform unit is used to perform frequencyspectrum transform for the one-time-extracted N sampling points of thedata and output the transformed data into the interference eliminationunit and the interference elimination control unit;

said interference elimination unit is used to perform interferenceelimination processing for the data of the points based on theidentification information of the points output from the interferenceelimination control unit and then the processed data will be sent to thefrequency spectrum inverse transform unit;

said frequency spectrum inverse transform unit is used to performfrequency spectrum inverse transform for the data output from theinterference elimination unit and then output them;

said interference elimination control unit is used to get the energyaccumulation of individual data after transform for M times for the Nsampling points and obtain N energy values, wherein M≧1, remove partialexcessive large values and average the rest, compute the threshold valuebased on the average value and compare the threshold with the N energyvalues, then output the identification information of the points thathave energy values exceeding the threshold value to the interferenceelimination unit.

Additionally, the above device also possesses the followingcharacteristics: said interference elimination control unit furthercomprises an energy computation subunit, a data selection subunit, athreshold computation subunit and an interference determination subunit,wherein:

the energy computation subunit is used to compute the energy values of Npoints of the data after frequency spectrum transform and output theresult to the interference determination subunit and the data selectionsubunit;

the data selection subunit is used to sequence the energy values of Npoints of the data, remove partial excessive large energy values andthen output the energy values to the threshold computation subunit;

the threshold computation subunit is used to average the remainingenergy values and calculate the threshold for interference determinationbased on the computed average value and then output the threshold valueto the interference determination subunit;

the interference determination subunit is used to compare the N energyvalues with the threshold value, and then output the identificationinformation of the points that have energy values exceeding thethreshold value to the interference elimination unit.

Additionally, the above device also possesses the followingcharacteristics: said interference elimination control unit furthercomprises an energy computation subunit, an energy accumulation subunit,a data selection subunit, a threshold computation subunit, aninterference determination subunit and an interference record subunit,wherein:

said energy computation subunit is used to compute the energy values ofN points of the data after frequency spectrum transform and output theresult to the energy accumulation subunit;

said energy accumulation subunit is used to respectively accumulate theenergy values of N sampling points of the data within a set accumulationtime period to obtain N accumulated energy values and output the resultto the data selection subunit and the interference determinationsubunit;

said data selection subunit is used to sequence the N accumulated energyvalues, remove partial excessive large energy values and then output theenergy values to the threshold computation subunit;

said threshold computation subunit is used to average the remainingaccumulated energy values, calculate the threshold for interferencedetermination based on the computed average value and then output thethreshold value to the interference determination subunit;

said interference determination subunit is used to compare the Naccumulated energy values with the threshold value, and then output theidentification information of the points that have energy valuesexceeding the threshold value to the interference record subunit;

said interference record subunit is used to record the pointidentification information output from the interference determinationsubunit and send the information to the interference elimination unitwhen the next accumulation time period starts;

moreover, said interference elimination unit performs interferenceelimination processing for the data of the corresponding points withinthe current accumulation time period based on the identificationinformation of points output from the interference record subunit in thelast accumulation time period.

Additionally, the above method also possesses the following features:the data selection subunit removes K largest energy values from said Nenergy values; K is pre-set in this subunit and can be obtained in thefollowing method:

$\begin{matrix}{K = {{ceil}( {\sum\limits_{i = 1}^{N_{li}}{\frac{f_{li}}{f_{s}}*N}} )}} &  a )\end{matrix}$wherein, N_(I) is the estimated number of narrow-band interferences;f_(Ii) is the estimated bandwidth of the i^(th) narrow-bandinterference; f_(S) is the sampling frequency of the input data, “ceil ()” means rounding towards plus infinity;

b) K is the integer that is larger than 0.25N and less than 0.35N;

c) K is set as N−1, which means that the data selection subunit selectsthe minimum energy value for output.

Additionally, said device also comprises the following characteristics:said interference record subunit will also count the number K of pointswhich have larger energy values than the threshold and send it to thedata selection subunit, which will output the result after removing Klargest energy values from said N energy values.

Additionally, said device also possesses the following characteristics:said data selection subunit removes not only partial excessive largeenergy values, but also excessive small energy values as well, and thenoutputs the remaining energy values.

Additionally, said device also possesses the following feature: in saidthreshold computation subunit, said average value is multiplied with3-3.5 to be the threshold value.

Additionally, said device also possesses the following characteristics:when said interference elimination unit suppresses interference for dataat interference points, it reduces the energy value of the data atinterference points to the time average value of the minimum energyvalue within said N energy values, or it reduces the energy value of thedata at interference points to the time average value of said averagevalues.

The present invention aims at eliminating narrow-band interference in aspread spectrum communication system and processes the signals withinthe frequency domain. The designed interference determination thresholdis used to sequence the estimated power spectrum or the frequencyspectrum according to their energy or amplitude values, eliminate theimpact of larger energy values. Therefore the obtained threshold willnot change greatly due to the number and the amplitude of thenarrow-band interferences, neither will it increase as the energy andthe number of the narrow-band interferences increase. As a result, itcould reflect the real performance of non-interference data andcorrectly distinguish the interference data from non-interference datawithout ignoring those original interference data, thus ensuring thatthe performance of suppressing interference remains stable when theinterference situation changes.

BRIEF DESCRIPTION OF FIGURES

FIG. 1 is a schematic diagram of energy of frequency spectrum of generalspread spectrum signals.

FIG. 2 is a schematic diagram of the structure of thereceived-signal-processing device in the first embodiment of the presentinvention.

FIG. 3 is a schematic diagram of the structure of the interferenceelimination device in FIG. 2.

FIG. 4 is a schematic diagram of the structure of the interferenceelimination device in the second embodiment in the present invention.

PREFERRED EMBODIMENTS OF THE INVENTION

The present invention will be further described in detail with referenceto the attached figures and the embodiments.

The First Embodiment

FIG. 2 is a schematic diagram of the structure of thereceived-signal-processing device in the embodiment of the presentinvention, which comprises radio frequency converter 100, digitalquantizer 110, digital down converter and processor 120, interferenceelimination device 130, and automatic gain processor 140.

The signals are received through the radio frequency converter 100 andconverted into digital signals after being sampled through digitalquantizer 110, then the signals are input into the digital downconverter and processor 120 to be intermediate frequency (IF) signals.The output IF signals will be input into interference elimination device130 for interference elimination processing and after the interferencesuppression, the data will be sent to automatic gain processor 140 forautomatic gain control and finally be transmitted to the base-band forprocessing.

For the design of the location for interference elimination device 130,the device could either be placed before automatic gain controller 140or at the place where the base-band processing is performed. In thepresent embodiment, it is chosen to be placed before automatic gaincontroller 140, because with the existence of the narrow-bandinterference, the signal energy will be much higher than the normalvalue, thus prohibiting the automatic gain controller 140 fromperforming gain control normally with respect to non-interferencesignals. When the interference is fairly high, the automatic gaincontroller 140 will be in saturated status and stop working. Thereforethe selection of the location for interference elimination device 130 isan important factor in the design.

The above figure is only an example, and in fact other devices couldalso be added between individual devices.

As shown in FIG. 3, interference elimination device 130 furthercomprises the following units:

a frequency spectrum transform unit 131 used to perform frequencyspectrum transform for the one-time-extracted N sampling points of thedata, obtain, the spectrum of the data and output the transformed datainto the interference elimination unit and the interference eliminationcontrol unit;

an interference elimination unit 132 used to perform data interferencesuppression, and based on the received identification information of thepoints output from interference elimination control unit, degrade theenergy values of these points to the noise level and send the N pointsof data after the interference elimination processing to frequencyspectrum inverse transform unit;

a frequency spectrum inverse transform unit 133 used to performfrequency spectrum inverse transform for the N points of data outputfrom the interference elimination unit and then output them;

an interference elimination unit 134 used to compute the data energyvalues that are received at N sampling points, remove K largest energyvalues and average the rest, compute the threshold based on the averagevalue and compare the threshold with the N energy values, and thenoutput the identification information of the points that have energyvalues exceeding the threshold value to the interference eliminationunit.

The interference elimination control unit further comprises thefollowing parts:

an energy computation subunit 1341 used to compute the energy values ofN points of the data after frequency spectrum transform and output theresult to the data selection subunit and the interference determinationsubunit;

a data selection subunit 1342 used to sequence the energy values of Npoints of the data, remove K largest energy values and output theremaining values to the threshold computation subunit;

a threshold computation subunit 1343 used to compute the average energyvalue for the remaining N-K energy values of the data and calculate thereasonable threshold for interference determination based on thecomputed average value, and then output the threshold value to theinterference determination subunit;

an interference determination subunit 1344 used to compare the N energyvalues with the threshold value, and then identify those points thathave larger energy values than the threshold values as the interferencepoints, then finally output the identification information of thosepoints to the interference elimination unit.

Based on said interference elimination device 130, in the presentembodiment, the method for eliminating narrow-band interference in aspread spectrum system comprises following steps of:

step A, extracting the data of N sampling points to perform frequencyspectrum transform each time and obtaining the transformed data of Npoints;

the present embodiment uses the FFT (Fast Fourier Transform) to obtainthe estimation for data power spectrum. However there are other ways aswell, such as cosine transform and wavelet transform, etc.

The chosen number N of the points is related to the minimum narrow-bandinterference bandwidth which can be identified. In the embodiment of thepresent invention, the bandwidth of the spread spectrum signal is 1.2288MHz; the data sampling rate is 2*1.2288 MHz. In order to distinguish thenarrow-band interference of 30 kHz, it needs at least2*1.2288*10E6/(30*10³)=81.92 points, namely FFT of 128 points.Obviously, the more points of FFT, the higher capability fordistinguishing the narrow-band interference, which in return requires agreater amount of computation in hardware implementation, therefore, wecan select the value of N based on the system and the requirements forthe identification accuracy of narrow-band interference. In the presentembodiment, N=256 can be chosen.

step B, computing the modulus square for the data of N points aftertransform, namely getting the energy values of the data to obtain theestimation value for the data power spectrum;

Step C, sequencing the energy values for the N points of the data,either in the order from small to large or from large to small, and thenremoving K largest energy values.

In the case of narrow-band interference elimination in a certainspecific region, sometimes location and quantity of the interference canbe determined according to the condition of the region, such as thecharacteristic of narrow-band signals obtained by frequencypre-sweeping. Then the number of the data occupied by the interferencescan be computed according to the bandwidth and the number of theinterferences, thus determining the number K of the points that needs tobe removed and presetting it in the system. The calculation formula isas follows:

$\begin{matrix}{K = {{ceil}( {\sum\limits_{i = 1}^{N_{li}}{\frac{f_{li}}{f_{s}}*N}} )}} & (1)\end{matrix}$

wherein N_(I) is the number of narrow-band interferences; f_(Ii) isbandwidth of the i^(th) narrow-band interference; f_(S) is samplingfrequency of the input data, “ceil ( )” means rounding towards plusinfinity.

In another embodiment, in order to simplify the design, the value of Kin the system could be pre-set as the integer that is larger than 0.25Nand less than 0.35N, for example, set as ceil ((⅓)*N). The reason forsuch setting is that while designing a narrow-band interferenceelimination system, if the entire bandwidth of the interference exceeds30% of the signal bandwidth, the interference elimination system hasalready failed due to too much data interfered. Therefore, choosing thisvalue based on the system design ability can ensure that the averagevalue will not change due to the impact of the interference within thesystem capability scope, meanwhile can ensure the accuracy of theaverage value to a certain extent.

Step D, averaging the energy values for the remaining (N-K) points ofdata, and computing the threshold value for determining the narrow-bandinterference based the obtained average value.

It should be noted that the term “averaging” in the text is not limitedto arithmetic mean, but it can also be weighted mean, geometric mean ormiddle value, etc.

When choosing the threshold, it needs to ensure that the data withoutinterference will not be considered as interference, namely thethreshold should not be too small; moreover, the data with interferenceshould be guaranteed to be suppressed, namely the threshold should notbe too large. Generally speaking, the CDMA signals could be approximatedas white noise and its energy distribution is approximately χ′distribution, so a value that is 2-4 times, more preferably 3-3.5 times,of the average value can be taken as the threshold. However, the methodof computing threshold value from an average value in the presentinvention is not limited to the method described above, any knownalgorithms can be used.

Step E, comparing the energy values of the N points of data with thethreshold value, performing interference suppression for the points ofdata that have energy values exceeding the threshold, and degrading theenergy value to the noise level;

Noise level is a statistic. The average value of the data during acertain time period could be treated as the estimation of the noiseaverage. Without narrow-band interference, the data will generallysatisfy the Gauss distribution, thus the estimation is unbiased.However, with the existence of the narrow-band interference, the datawill no longer satisfy the Gauss distribution, therefore choosing theaverage value of all the data to be the “noise level” doesn't workproperly. In the present embodiment, the minimum energy value of N dataenergy values is preferably chosen as the noise level standard. However,in another embodiment, the average value calculated from the steps abovecan also be chosen as the noise level standard, or the data energyvalues at interference points can also be degraded to zero. However, theoriginal useful information is also removed totally, thus causing agreat damage to the original data.

Step F, performing frequency spectrum inverse transform for the dataafter interference elimination processing and then outputting the data.

The Second Embodiment

The structure of received-signal-processing device in this embodiment isthe same as in the first embodiment. However, when the interferenceelimination processing device in this example determined the location ofthe point with interference, it uses the energy value that isaccumulated in an accumulation time period as the basis, and theinformation of these points is used for interference elimination in thenext accumulation time period. By doing this, it could reduce the amountof the calculation as well as the requirements for real-timeimplementation of the hardware. Furthermore, while removing the Kaccumulated energy values in the present embodiment, the value of K isnot pre-set, but is set based on the determination result from the lastaccumulation time period.

FIG. 4 is a schematic diagram for the interference elimination device inthe present embodiment, wherein the frequency spectrum transform unit131 and the frequency spectrum inverse transform unit 133 are the sameas in the first embodiment and will not be discussed anymore. While theinterference elimination control unit 234 is used within an accumulationtime period to respectively compute the accumulated energy values of Nsampling points of the data, remove the K largest energy values andaverage the rest, determine a threshold based on the obtained averagevalue and compare it with the N accumulated energy values, and thenrecord the identification information of the points that have energyvalues exceeding the threshold value and finally output the informationto the interference elimination unit 133. Based on the receivedidentification information, the interference elimination unit willperform interference elimination processing for the corresponding pointswithin the next accumulation time period.

As it is shown in FIG. 4, an energy accumulation subunit and aninterference record subunit are added in the interference eliminationcontrol unit 234 which comprises in detail:

an energy computation subunit 2341 used to compute the energy values ofN points of data after frequency spectrum transform and output theresult to the energy accumulation subunit;

an energy accumulation subunit 2342 used to respectively accumulate theenergy values for the data at N sampling points within a setaccumulation time period and get the accumulated energy values of Npoints and output the values to the data selection subunit andinterference determination subunit;

a data selection subunit 2343 used to sequence N accumulated energyvalues, remove the K largest energy values and output the values intothreshold computation subunit. K is selected as the number of pointsthat have energy values exceeding the threshold in the last accumulationtime period according to the information output from the interferencerecord subunit;

a threshold computation subunit 2344 used to compute the average valuefor the remaining N-K accumulated data energy values and calculate areasonable threshold for interference determination based on thecomputed average value and then output the threshold value to theinterference determination subunit;

an interference determination subunit 2345 used to compare the Naccumulated energy values with the threshold value, and then identifythose points that have larger energy values than the threshold values asthe interference location points, finally output the identificationinformation of those points to the interference record subunit;

an interference record subunit 2346 used to record the identificationinformation of the interference points that is output from theinterference determination subunit and send the result to theinterference elimination unit when the next accumulation time periodstarts, and meanwhile count the number of the points and output theresult to the data selection subunit.

Correspondingly, based on the identification information of theinterference points that is output from the interference record subunitin the last accumulation time period, the interference elimination unit232 is used to perform interference elimination processing for the dataof corresponding points in the current accumulation time period, namelydegrades its energy value to the noise level and finally outputs.

Correspondingly, there are some differences between the method ofeliminating narrow-band interference in the spread spectrum system inthis embodiment and that in the first embodiment, including thefollowing steps:

Step 1, extracting data of N sampling points to perform frequencyspectrum transform each time to obtain the transformed data of N points,and getting the energy values for the data after transform;

Meanwhile performing information update processing and interferenceelimination processing simultaneously, wherein the information updateprocessing comprises following steps:

step 2, within a set accumulation time period, accumulating the dataenergy values for M times for the N sampling points of the datarespectively and obtaining N accumulated energy values, wherein M is aninteger which is greater than or equal to 1 and is determined by thenumber of sampling cycles included within a accumulation time period.When M=1, it means getting the energy values of the data for once;

Accumulation could make the estimated result closer to the real powerspectrum, thus reflect more truthful characteristics of the data. Thetime duration of an accumulation time period should, on one hand,guarantee that the power spectrum obtained in the accumulation timeperiod is stable, so the time duration should not be too short, and onthe other hand, also guarantee that the characteristics of thenarrow-band interference will not change dramatically within this timeperiod and ensure that the estimated result of the power spectrum canreflect the changes of the narrow-band interference of spread spectrumsignals in time. So the time duration should not be too long. Generallyspeaking, the time duration for narrow-band interference is measured inseconds, so the accumulation time period could be chosen as 60-120 ms,and this value will not greatly impact on the reaction capability of thesystem for the narrow-band interference.

step 3, sequencing N accumulated energy values and removing K largestenergy values. K is selected as the number of points that haveaccumulated energy values exceeding the threshold in the lastaccumulation time period;

Here, K is determined by using priori information in the lastaccumulation time period. It could accurately avoid the impacts of theinterference on the average value, thus ensuring that the thresholdvalue will not change under the influence of interference.

step 4, computing the average energy value for the remaining N-Kaccumulated data energy values and calculating the threshold forinterference determination based on the computed average value. Here, avalue that is 3-3.5 times of the average value is also taken as thethreshold value;

step 5, comparing the N accumulated energy values with the thresholdvalue, and recording the identification information and number of thepoints that have accumulated energy values exceeding the thresholdwithin the present accumulation time period and meanwhile removing therecords of other points.

After step 1, the following steps for interference eliminationprocessing are performed simultaneously:

step 2′, for the N points of data that are obtained from frequencyspectrum transform each time within the current accumulation timeperiod, finding the points corresponding to the interferences that arerecorded in the last accumulation time period and adjusting the energyvalues of the data at these points to the noise level;

The noise level in the present embodiment uses the minimum value of theN accumulated energy values divided by the accumulation times to be thenoise level, namely, to degrade the energy value of the interferencedata to the minimum value after time averaging. Said average value thatis calculated from previous steps can also be chosen to be divided bythe accumulation times, namely after time averaging, to be the noiselevel.

step 3′, performing frequency spectrum inverse transform for theadjusted data and outputting the result, ending.

Many variations and modification can be made based on said twoembodiments above:

For example, in the two said embodiments, the average value is obtainedby removing K points that have the largest energy values from the Npoints of data and averaging the rest, based on this average value thethreshold is computed, thus avoiding the impacts on the thresholdcomputation from interference signals with larger energies. Based on theabove contents, another two embodiments with following changes can beobtained: after removing K points that have the largest energy valuesfrom the N points of data, then deleing L points that have the minimumenergy values, and then averaging the remaining N-K-L energy values ofthe data, namely, selecting parts of the data in the middle positionsafter sequencing, while removing the excessively large and small data.

For another example, based on the device structures and method stepswithin the first and second embodiments, only the calculation method forthe threshold value is modified and then another two embodiments can beobtained, in which after getting N energy values (accumulated ornon-accumulated), the data selection subunit selects either the minimumenergy value or an accumulated energy value which then multiplies with acoefficient to obtain a threshold value for interference determination,for example, the threshold value is 2-4 times, such as 3-3.5 times, ofthe minimum value. In such a way, the impacts on the thresholdcomputation from excessive large energy values produced by interferencecan also be avoided.

In summary, as regards eliminating narrow-band interference in thespread spectrum communication system, the present invention processesthe signals within the frequency domain. For the designed threshold forinterference determination, it is to sequence the estimated spectrum ofthe data according to their energy values (namely the squares of theamplitudes) and exclude the impacts of excessively large energy valueson threshold computation. Therefore, the obtained threshold value willnot vary greatly under the influence of the magnitude and the number ofnarrow-band interferences, neither will it increase when the energy andthe quantity of the narrow-band interference increase. Therefore it canreflect the real level of non-interference data, as well as accuratelydistinguish between the interference and non-interference data.Meanwhile, it will never lead to the ignorance of the data that isoriginally interference, thus ensuring that the performance of theinterference suppression can be still stable even when the interferencesituation changes.

INDUSTRIAL APPLICABILITY

The present invention has already been realized in the CDMA_(—)20001xbackward link. After the simulation, with the existence of both largeenergy narrow-band interference and multiple narrow-band interferences,it greatly increases the suppression capability of the interferencesuppression system and improves the system performance. The presentinvention is a general technology, and can be used for obtainingthreshold value in the technology for eliminating narrow-bandinterference in any spread spectrum system.

1. A method for eliminating narrow-band interference in a spreadspectrum system, comprising the following steps of: (A) extracting dataof N sampling points to perform frequency spectrum transform each timeand obtaining transformed data of N points; (B) for the N samplingpoints, getting an energy accumulation of individual data aftertransform for M times and obtaining N energy values, wherein M is aninteger greater than or equal to 1; (C) removing partial excessive largevalues from said N energy values and averaging remaining energy valuesto get an average value, calculating a threshold value for interferencedetermination based on the average value; (D) comparing said N energyvalues with the threshold value, and obtaining identificationinformation of all points that have energy values exceeding thethreshold value; (E) based on the identification information of saidpoints, performing interference suppression for the data ofcorresponding points after frequency spectrum transform, performingfrequency spectrum inverse transform for processed data and thenoutputting; wherein step (C) is first to sequence said N energy valuesand remove K largest energy values, and K is computed in one offollowing methods: $\begin{matrix}{K = {{ceil}( {\sum\limits_{i = 1}^{N_{li}}{\frac{f_{li}}{f_{s}}*N}} )}} &  a )\end{matrix}$  wherein, N_(I) is estimated number of narrow-bandinterference; f_(Ii) is estimated bandwidth of i^(th) narrow-bandinterference; f_(S) is sampling frequency of input data, “ceil ( )”means rounding towards plus infinity; b) K is an integer that is largerthan 0.25N and less than 0.35N; c) K is a number of values that arelarger than the threshold value in the N energy values in lastcomputation; d) K=N−1, i.e., directly using minimum energy value as saidaverage value.
 2. The method in claim 1, wherein said step (C) removesnot only partial excessive large energy values, but also excessive smallenergy values as well, and then averages the remaining energy values. 3.The method in claim 1, wherein said step (C) uses said average valuemultiplied with 3-3.5 to be said threshold value.
 4. The method in claim1, wherein in said step (B), M is determined by a number of samplingcycles included in an accumulation time period, and in said step (E)when processing interference elimination for data in an accumulationtime period, the points in which the interference suppression is neededto be performed are determined based on the identification informationof the points whose energy values are larger than said thresholdrecorded in a last accumulation time period.
 5. The method in claim 1,wherein said accumulation time period is of 60-120 ms.
 6. The method inclaim 1, wherein in step (E) when performing interference suppressionfor the data, energy values of data at interference points are reducedto time average value of the minimum energy value within said N energyvalues, or the energy values of data at interference points are reducedto time average value of said average value.
 7. A device for eliminatingnarrow-band interference in a spread spectrum system, characterized inthat it comprises a frequency spectrum transform unit, an interferenceelimination unit, an interference elimination control unit and afrequency spectrum inverse transform unit, wherein: said frequencyspectrum transform unit is used to perform frequency spectrum transformfor one-time-extracted N sampling points of data and output transformeddata to the interference elimination unit and the interferenceelimination control unit; said interference elimination unit is used toperform interference elimination processing on data of points based onidentification information of these points output from the interferenceelimination control unit and then send processed data to the frequencyspectrum inverse transform unit; said frequency spectrum inversetransform unit is used to perform frequency spectrum inverse transformfor the data output from the interference elimination unit and thenoutput them; said interference elimination control unit is used to getan energy accumulation of individual data after transform for M timesfor the N sampling points to obtain N energy values (M≧1), remove Kexcessive large values and average remaining energy values to get anaverage value, compute a threshold value based on the average value andcompare the threshold value with the N energy values, and then outputthe identification information of the points that have energy valuesexceeding the threshold value to the interference elimination unit;wherein K is computed in one of following methods: $\begin{matrix}{K = {{ceil}( {\sum\limits_{i = 1}^{N_{li}}{\frac{f_{li}}{f_{s}}*N}} )}} &  a )\end{matrix}$  wherein, N_(I) is estimated number of narrow-bandinterference; f_(Ii) is estimated bandwidth of i^(th) narrow-bandinterferences; f_(S) is sampling frequency of input data, “ceil ( )”means rounding towards plus infinity; b) K is an integer that is largerthan 0.25N and less than 0.35N; c) K is a number of values that arelarger than the threshold value in the N energy values in lastcomputation; d) K=N−1, i.e., directly using minimum energy value as saidaverage value.
 8. The device for eliminating narrow-band interference inclaim 7, characterized in that the interference elimination control unitfurther comprises an energy computation subunit, a data selectionsubunit, a threshold computation subunit and an interferencedetermination subunit, wherein: the energy computation subunit is usedto compute energy values of N points of data after frequency spectrumtransform and output the energy values to the interference determinationsubunit and the data selection subunit; the data selection subunit isused to sequence the energy values of N points of data, remove Kexcessive large energy values and then output to the thresholdcomputation subunit; the threshold computation subunit is used toaverage the remaining energy values to obtain an average value andcalculate a threshold value for interference determination based on theobtained average value and then output the threshold value to theinterference determination subunit; the interference determinationsubunit is used to compare the energy values of N points of data withthe threshold value, and then output the identification information ofthe points that have energy values exceeding the threshold value to theinterference elimination unit.
 9. The device in claim 8, characterizedin that said interference record subunit will also count a number ofpoints, K, which have larger energy values than the threshold value, andoutput the number to the data selection subunit, wherein said dataselection subunit removes K largest energy values from said N energyvalues and then output.
 10. The device in claim 8, wherein said dataselection subunit removes not only partial excessive large energyvalues, but also excessive small energy values, and then outputs theremaining energy values.
 11. The device in claim 8, wherein saidthreshold computation subunit uses said average value multiplied with3-3.5 as the threshold value.
 12. The device for eliminating narrow-bandinterference in claim 7, characterized in that said interferenceelimination control unit further comprises an energy computationsubunit, an energy accumulation subunit, a data selection subunit, athreshold computation subunit, an interference determination subunit andan interference record subunit, wherein: said energy computation subunitis used to compute the energy values of N points of data after frequencyspectrum transform and output the energy values to the energyaccumulation subunit; said energy accumulation subunit is used torespectively accumulate the energy values of N sampling points of datawithin a set accumulation time period and obtain N accumulated energyvalues and output them to the data selection subunit and theinterference determination subunit; said data selection subunit is usedto sequence the N accumulated energy values, remove K excessive largeenergy values and then send the energy values to the thresholdcomputation subunit; said threshold computation subunit is used toaverage the remaining accumulated energy values to obtain an averagevalue and calculate a threshold value for interference determinationbased on the obtained average value and then output the threshold valueto the interference determination subunit; said interferencedetermination subunit is used to compare the N accumulated energy valueswith the threshold value, and then output the identification informationof the points that have energy values exceeding the threshold value tothe interference record subunit; said interference record subunit isused to record the identification information of the points output fromthe interference determination subunit and output the information to theinterference elimination unit when next accumulation time period starts;Moreover, said interference elimination unit performs interferenceelimination processing for the data of corresponding points withincurrent accumulation time period based on the identification informationof the points output from the interference record subunit in lastaccumulation time period.
 13. The device in claim 12, characterized inthat said interference record subunit will also count a number ofpoints, K, which have larger energy values than the threshold value, andoutput the number to the data selection subunit, wherein said dataselection subunit removes K largest energy values from said N energyvalues and then output.
 14. The device in claim 12, wherein said dataselection subunit removes not only partial excessive large energyvalues, but also excessive small energy values, and then outputs theremaining energy values.
 15. The device in claim 12, wherein saidthreshold computation subunit uses said average value multiplied with3-3.5 as be the threshold value.
 16. The device for eliminatingnarrow-band interference in claim 7, wherein when said interferenceelimination unit suppresses interference for data at interferencepoints, it reduces the energy values of the data at interference pointsto time average value of minimum energy value in said N energy values orit reduces the energy values of the data at interference points to timeaverage value of said average values.